The AI Frontier in Molecular Modelling and Drug Designing aims to provide a comprehensive guide on the application of AI concepts in drug designing, discovery, and molecular modeling. The book delves into machine and deep learning techniques that predict structural properties of molecules, identify druggable pockets, and assess physicochemical properties of targets. Sections explore current and potential computational resources to tackle complex biological challenges. Each chapter is enriched with relevant examples, text boxes, and case studies that illustrate the practical application of AI techniques, their outcomes, and the challenges faced during implementation.

This resource is tailored for researchers, students, and professionals in both academia and industry, providing them with the latest methodologies, advancements in technology, and practical insights into AI-driven drug research, structural biology, computational biology, and translational science.

• Provides the latest concepts of Artificial Intelligence, methodologies, and technological advancements in drug research
• Covers a wide range of topics, including protein structure prediction and molecular docking methods, bridging Artificial Intelligence technology with pharmaceutical sciences for translational research
• Includes detailed practical applications of AI, with case studies demonstrating how AI-driven approaches expedite drug discovery and molecular modeling processes